Automated Inundation Mapping Over Large Areas Using Landsat Data and Google Earth Engine

Inman, Victoria L.; Lyons, Mitchell

doi:10.3390/rs12081348

Cited by 39 publications

(30 citation statements)

References 39 publications

(105 reference statements)

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“…The vertical separation between the anemometer and the CH 4 analyser was approximately 0.0 m (i.e. middle points of the sonic and optical paths in the same horizontal plane) and the lateral separation, in the crosswind plane, was approximately 0.3 m. Standard meteorological variables were measured: [35,36]. (Online version in colour.)…”

Section: (B) Instrumentationmentioning

confidence: 99%

From sink to source: high inter-annual variability in the carbon budget of a Southern African wetland

Helfter

Gondwe

Murray-Hudson

et al. 2021

Phil. Trans. R. Soc. A.

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We report on three years of continuous monitoring of carbon dioxide (CO 2 ) and methane (CH 4 ) emissions in two contrasting wetland areas of the Okavango Delta, Botswana: a perennial swamp and a seasonal floodplain. The hydrographic zones of the Okavango Delta possess distinct attributes (e.g. vegetation zonation, hydrology) which dictate their respective greenhouse gas (GHG) temporal emission patterns and magnitude. The perennial swamp was a net source of carbon (expressed in CO 2 -eq units), while the seasonal swamp was a sink in 2018. Despite differences in vegetation types and lifecycles, the net CO 2 uptake was comparable at the two sites studied in 2018/2020 (−894.2 ± 127.4 g m −2 yr −1 at the perennial swamp, average of the 2018 and 2020 budgets, and −1024.5 ± 134.7 g m −2 yr −1 at the seasonal floodplain). The annual budgets of CH 4 were however a factor of three larger at the permanent swamp in 2018 compared to the seasonal floodplain. Both ecosystems were sensitive to drought, which switched these sinks of atmospheric CO 2 into sources in 2019. This phenomenon was particularly strong at the seasonal floodplain (net annual loss of CO 2 of 1572.4 ± 158.1 g m −2 ), due to a sharp decrease in gross primary productivity. Similarly, drought caused CH 4 emissions at the seasonal floodplain to decrease by a factor of 4 in 2019 compared to the previous year, but emissions from the perennial swamp were unaffected. Our study demonstrates that complex and divergent processes can coexist within the same landscape, and that meteorological anomalies can significantly perturb the balance of the individual terms of the GHG budget. Seasonal floodplains are particularly sensitive to drought, which exacerbate carbon losses to the atmosphere, and it is crucial to improve our understanding of the role played by such wetlands in order to better forecast how their emissions might evolve in a changing climate. Studying such hydro-ecosystems, particularly in the data-poor tropics, and how natural stressors such as drought affect them, can also inform on the potential impacts of man-made perturbations (e.g. construction of hydro-electric dams) and how these might be mitigated. Given the contrasting effects of drought on the CO 2 and CH 4 flux terms, it is crucial to evaluate an ecosystem's complete carbon budget instead of treating these GHGs in isolation. This article is part of a discussion meeting issue ‘Rising methane: is warming feeding warming? (part 2)’.

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Section: (B) Instrumentationmentioning

confidence: 99%

From sink to source: high inter-annual variability in the carbon budget of a Southern African wetland

Helfter

Gondwe

Murray-Hudson

et al. 2021

Phil. Trans. R. Soc. A.

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“…Spectral indices derived from Landsat data combine reflectances from multiple image bands that enable the detection of specific surface characteristics. Many studies have mapped inundation extent by quantifying optimal thresholds of spectral indices for local conditions (Inman & Lyons, 2020; Thomas et al, 2015). The modified normalized difference water index (MNDWI) often provides the best predictions of open water (Ji et al, 2009; Xu, 2006).…”

Section: Introductionmentioning

confidence: 99%

Remote sensing to characterize inundation and vegetation dynamics of upland lagoons

et al. 2022

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Understanding broad trends in the distribution and composition of wetlands is essential for making evidence‐based management decisions. Determining temporal change in the extent of inundation in wetlands using remote sensing remains challenging and requires on‐ground verification to determine accuracy and precision. Therefore, optimization and validation of remote sensing methods in threatened wetlands is a high priority for their conservation. Despite their ecological importance in the landscape, we have little knowledge of the variation in the spatial extent of inundation in upland lagoons, a threatened ecological community in New South Wales, Australia. Our project developed locally trained algorithms to predict the extent of water and emergent vegetation using imagery from the Landsat‐5, ‐7, and ‐8 satellites. The best model for upland lagoons used shortwave infrared reflectance (performing better than normalized difference spectral indices), with model accuracy against validation transects greater than 95%. We applied the model to images from 1988 to 2020 across 58 lagoons to generate a dataset that demonstrates the variable water regime and vegetation change in response to local rainfall over 32 years such as in the lagoons. Our results reduce threats to a dynamic threatened ecological community by filling an important knowledge gap and demonstrate a valuable method to understand historical and current changes in the hydrology of dynamic wetland systems more broadly.

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“…The emergence of cloud-based geospatial processing platforms such as Google Earth Engine (GEE) provides an efficient means for rapid access and combined analysis of multi-source data [26]. The capability of accurate flood mapping within minutes was achieved by analyzing hundreds of Sentinel-1 SAR and Landsat images archived on the GEE [27][28][29]. In addition to exploiting a growing number of observations from current satellite sensors through big data techniques, planned next generation satellite missions including the NASA-ISRO Synthetic Aperture Radar (NISAR) and NASA-CNES SWOT radar altimetry missions will enable further enhancement in global water cycle and flood assessment leveraging satellite river gauging and high spatial-temporal resolution observations [30][31].…”

Section: Introductionmentioning

confidence: 99%

Satellite Flood Inundation Assessment and Forecast Using SMAP and Landsat

Kimball

Sheffield

et al. 2021

IEEE J. Sel. Top. Appl. Earth Observations Remote Sensing

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The capability and synergistic use of multi-source satellite observations for flood monitoring and forecasts is crucial for improving disaster preparedness and mitigation. Here, surface fractional water cover (FW) retrievals derived from Soil Moisture Active Passive (SMAP) L-band (1.4 GHz) brightness temperatures were used for flood assessment over southeast Africa during the Cyclone Idai event. We then focused on five sub-catchments of the Pungwe basin and developed a machine learning-based approach with the support of Google Earth Engine (GEE) for daily (24-hour) forecasting of FW and 30-m inundation downscaling and mapping. The Classification and Regression Trees (CART) model was selected and trained using retrievals derived from SMAP and Landsat coupled with rainfall forecasts from the NOAA Global Forecast System (GFS). Independent validation showed that FW predictions over randomly selected dates are highly correlated (R=0.87) with the Landsat observations. The forecast results captured the flood temporal dynamics from the Idai event; and the associated 30-m downscaling results showed inundation spatial patterns consistent with independent satellite Synthetic Aperture Radar (SAR) observations. The data-driven approach provides new capacity for flood monitoring and forecasts leveraging synergistic satellite observations and big data analysis, which is particularly valuable for data sparse regions.

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Automated Inundation Mapping Over Large Areas Using Landsat Data and Google Earth Engine

Cited by 39 publications

References 39 publications

From sink to source: high inter-annual variability in the carbon budget of a Southern African wetland

From sink to source: high inter-annual variability in the carbon budget of a Southern African wetland

Remote sensing to characterize inundation and vegetation dynamics of upland lagoons

Satellite Flood Inundation Assessment and Forecast Using SMAP and Landsat

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